Blur correction techniques are techniques for detecting blur which occurs when a still image is captured, and reducing the blur occurring within the captured image by correction based on the detected amount of blur.
As methods of detecting blur, there are methods using a motion detection sensor (for example, an angular rate sensor such as a gyroscope, or an acceleration sensor, and so on) provided in the camera or methods involving detection by analyzing a captured image. Furthermore, optical correction or sensor shift correction in which blur is corrected by controlling the position of a lens or imaging device at the time of image-capturing as well as electronic correction in which blur is electronically corrected through image processing after image-capturing are available as methods of correcting blur.
In most optical correction or sensor shift correction methods, the occurrence of blur in a captured image is reduced by detecting the trajectory of blur at the time of image-capturing, using an angular rate sensor, and controlling the position of the lens or imaging device so as to cancel out the blur in the detected trajectory.
Meanwhile, a method of estimating a trajectory of blur by analyzing a captured image, and correcting the captured image into a blur-free image through image processing based on the estimated blur trajectory has been proposed (for example, see Non-Patent Literature 1 (NPL 1)). In the technique disclosed in NPL 1, the estimation of the trajectory of blur and the correction to a blur-free image are performed iteratively, using statistical information such as characteristics of a blur-free natural image or a property that should be satisfied by a flat region, thereby gradually bringing both the blur trajectory and the corrected image closer a desired result.
The principle for the occurrence of blur in a captured image and the principle behind the method of correcting blur through image processing after image-capturing shall be described with reference to FIG. 11. The occurrence of blur in a captured image is caused when a beam of light, which should have been image-captured by only one pixel when blur does not occur, is also distributed and captured by neighboring pixels.
Here, i (x, y) denotes a sharp image that is captured when blur does not occur (hereafter called “sharp image”). Furthermore, j (x, y) denotes a captured image in which blur has occurred. Furthermore, p (x, y) denotes a distribution function of a point image (point spread function (PSF)) when a light beam that should have been image-captured by only one pixel when blur does not occur also spreads to and is captured by neighboring pixels due to blurring. In this case, the relationship in Equation (1) below is true among i (x, y), j (x, y), and p (x, y).
                    [                  Math          .                                          ⁢          1                ]                                                                      j          ⁡                      (                          x              ,              y                        )                          =                              i            ⁡                          (                              x                ,                y                            )                                ⊗                      p            ⁡                          (                              x                ,                y                            )                                                          Equation        ⁢                                  ⁢                  (          1          )                    
Here, the symbol indicated below denotes a convolution operation, and (x, y) denotes a pixel position.
[Math. 2]

In addition, when the values of respective frequency components obtained when Fourier transform is performed on i (x, y), j (x, y), and p (x, y) are denoted as I (m, n), J (m, n), and P (m, n), the relationship in Equation (2) below is true among such values.[Math. 3]J(u,v)=I(u,v)×P(u,v)  Equation (2)
Here, (u, v) denotes the order of the frequency component. In this manner, on the frequency domain, the captured image is expressed by the product of the sharp image and the PSF. Inversely, if the PSF can be estimated by analyzing the captured image, the estimation result of a sharp image (hereafter called “corrected image”) can be calculated by dividing the captured image by the PSF on the frequency domain.
Furthermore, Patent Literature 1 (PTL 1) discloses a method of obtaining blur information using an angular rate sensor and performing correction processing. With this method, the PSF can be obtained without estimating the PSF from the captured image.
In addition, Patent Literature 2 (PTL 2) discloses a method of calculating PSF from angular rate data obtained through an angular rate sensor then generating an inverse filter from the PSF, and applying correction processing to a captured image. In this method, a smoothing unit which performs smoothing on the PSF and a control unit which controls the smoothing intensity of the smoothing unit according to the state of focus are provided, and thus it is possible to correct not only blur but also defocusing-related picture quality deterioration.